Data Scientist

The focus of the work will be developing, improving, and maintaining data science, machine learning, and data engineering models. Specifically, the data science will focus on Sales and Services Forecasting. In addition to the science and the tech, this will require the exploration and study of logistics planning processes within supply chain. Communication with diverse stakeholders is expected and crucial to identify key factors impacting logistic operations.

Requirements:

• Experience in forecasting problems and affinity with logistics and supply chain domain.
• Strong scientific background, business domain curiosity and proactive communication skills.
• Ability to write production-ready Python code, review PRs, and contribute to maintainable, usable, and extendable codebases.
• Experience with Machine Learning libraries and frameworks (e.g., XGBoost, scikit-learn, TensorFlow, PyTorch).
• Strong knowledge of cloud services, especially Google Cloud Platform (GCP), including Cloud Storage or BigQuery.
• Familiarity with open-source MLOps tools like Metaflow, BentoML, KubeFlow, or similar.
• Confidence in digging into code and understanding how things are working.
• Demonstrated ability to apply analytical findings to real-world business problems.
• Excellent problem-solving skills with a strategic mindset.Ideally, knowledge of Infrastructure as Code (IaC) tools like Terraform, automated testing and CI/CD tools like GitHub Actions.
• Ability to work in cross-functional teams with product owners, data scientists, backend engineers, and frontend engineers.

What 3 things from above are most important?

• Experience in forecasting problems especially in logistics and supply chain.
• Affinity with software engineering practices in the data science space.
• Cross-functional collaboration and teamwork.